Introduction
The United States automotive industry has shown exponential growth since its early stages in the late 19 th Century. The advancement of artificial intelligence was a major innovation for the development of automotive industry. Automated machines performed tasks that were previously being carried out by humans thereby minimizing rates of errors and improving the handling of repetitive tasks. However, the continuous advancement and adoption of automated machines such as robots have been found to have negative impacts on the economy (Groover, 2016). There exists a number of negative impacts of artificial intelligence on the economy.
The Negative Impacts of AI for the Economy
The emergence and advancement of Artificial intelligence has made the human workers obsolete. Humans have been displaced my artificial intelligence in the American manufacturing plants. The earliest robots were introduced in the American automotive factories in the 1960s, which were simple machines that carried out certain tasks such as handling heavy and hot die-cast parts. In the 1970s, the car factories worldwide speeded to catch up with the robotic in spot welding. These applications spread throughout the automotive world to handle expanded tasks. The major adoption of robots in the 1980s was to promote worker safety by giving repetitive and strenuous tasks to robots ( Elliott, 2019). The rapid advancement of automated machines followed afterwards and spread across the globe. In our contemporary society, robotics is surging in because it generates businesses with unbelievable efficiencies and savings. Additionally, the use of robots provides automotive companies with a competitive edge because they increase capacity and get rid of bottlenecks, they minimize warranty costs due to improved quality of cars, and protect workers from strenuous and dangerous tasks (Orr, 2016).
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Over the years, the US automotive industry has had a huge impact on the country’s domestic economy. The number of vehicles sold and the number of employees working in this industries were a sign of economic health. However, the increasingly rapid adoption of automated machines have caused significant negative impact on Americans. Reports reveals that many Americans have lost their jobs due to rapid adoption of robots in the industries that replaces them. Employment in the automotive industry has continued to decline since the 1990s and the trend is more likely to continue in the subsequent years. Evidence reveals that in the US, approximately 39 to 73 million jobs will be lost by the year 2030 ( Danner, 2019) .
According to Awad et al. (2018), automation has not only resulted in loss of jobs among many Americans, it has also led to wide gap between economic losers and winners. Income inequalities is bad for the economy because not every person will be able to contribute to the economic growth of the nation. Evidence reveals that technological advancement does not lead to economic growth and creation of wealth but rather it slows down the economy. Although the automotive companies may win through acquiring huge profits, experiences minimal errors, and faster production of products, many Americans may lose in terms of employment and lack of application of human skills (Groshen et al., 2019).
Conclusion
It is evident that technological advancement such as car manufacturing robotics has played a major role in the automotive industries like improving quality of cars manufactured and minimizes costs of production among others. However, the increased adoption and application of car manufacturing robots in the automotive industries is not healthy for the economy. It has resulted in increasing displacement of human skills rendering people jobless. Many Americans are currently jobless due to the adoption of robots and this has led to income inequality in the country. A huge income inequality slows down the economy because lack of employment means these populations are not able to contribute to the economic growth of the nations. Therefore, automated machines affect the economy in a negative way.
References
Awad, E., Levine, S., Kleiman-Weiner, M., Dsouza, S., Tenenbaum, J., Shariff, A., ... & Rahwan, I. (2018). Blaming humans in autonomous vehicle accidents: Shared responsibility across levels of automation. arXiv preprint arXiv:1803.07170 .
Danner, G. E. (2019). The Economic Case for Automation. In The Executive's How-To Guide to Automation (pp. 13-23). Palgrave Macmillan, Cham.
Elliott, A. (2019). The Culture of AI: Everyday Life and the Digital Revolution . Routledge.
Groover, M. P. (2016). Automation, production systems, and computer-integrated manufacturing . Pearson Education India.
Groshen, E. L., Helper, S., MacDuffie, J. P., & Carson, C. (2019). Preparing US workers and employers for an autonomous vehicle future. Retrieved from: https://avworkforce.secureenergy.org/wp-content/uploads/2018/06/Groshen-et-al-Report-June-2018-1.pdf
Orr, J. E. (2016). Talking about machines: An ethnography of a modern job . Cornell University Press.
